While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Role Overview:
The Senior Solutions Architect for AI Platforms will collaborate closely with customers to ideate innovative AI solutions tailored to solve complex business challenges. You will lead the end-to-end process from conceptualization through solution delivery, including detailed project roadmaps, resource planning, sprint execution strategies, and cost estimations. As a key leader within engagements, you will guide engineering teams, ensure high-quality delivery, and maintain transparent communication with clients.
Key Responsibilities:
Ideate and design AgenticAI and Gen AI solutions in collaboration with client stakeholders to address specific business needs.
Develop comprehensive project delivery plans, encompassing project roadmaps, resource allocations, sprint planning, and budgeting.
Lead technical teams through solution delivery, providing mentorship, technical oversight, and ensuring adherence to best practices.
Manage technical stakeholders, clearly communicating progress, risks, and mitigation strategies throughout the project lifecycle.
Govern overall solution delivery to ensure timely completion, high quality, and alignment with customer expectations.
Optimize GPU/compute utilization, storage, and networking for agentic workloads across dev, staging, and production. Operationalize GPU/CPU workloads on AWSÂ
Lead the Azure → AWS migration strategy for a large-scale agentic platform. Architect and deploy scalable infrastructure templates & shared services.
Required Qualifications:
Bachelor's degree in Engineering, Master's degree in Engineering or related discipline Preferred
Minimum 8 years of experience building and deploying scalable AI systems.
Experience designing and delivering Generative AI and Agentic AI solutions.
Key Competencies:
Excellent technical stakeholder management and communication skills.
Proven capability in first principles thinking, ownership, and strategic decision-making.
Strong expertise in cloud engineering, particularly AWS: EC2, EKS, Lambda, S3, CloudWatch, SageMaker, IAM, Route53. Must have driven cost optimization strategies across compute, storage, and data transfer on AWS.
MLOps - AWS Bedrock (AgentCore, foundation models), API Gateway, Cognito, IAM federation
Infrastructure as Code: Terraform, AWS CDK, or CloudFormation
Expertise with Docker, Kubernetes (EKS preferred), and scalable microservice deployments, ECS/Fargate, Lambda
Monitoring and logging setup for AI workloads (e.g., Prometheus, Grafana, CloudWatch), Observability (CloudWatch, Datadog, OpenTelemetry)
FinOps (Cost Explorer, CUR, token-level chargeback)
NVIDIA NIM/NGC model deployment
CI/CD & GitOps (GitLab, ArgoCD/Flux, CodePipeline)
MLOps - AWS Bedrock (AgentCore, foundation models), API Gateway, Cognito, IAM federation
End-to-end understanding of model lifecycle, from training to serving. Expert in model registry, versioning, lineage tracking, and deployment automation
Familiarity with Triton, TorchServe, or custom model inference patterns
Experience with cost tracking, budget alerts, and resource right-sizing in AWS
Proven ability to profile GPU/memory usage and optimize for cost-performance tradeoffs.
Preferred Skills:
Familiarity with LangGraph / LiteLLM Gateway.
Multi-cloud migration experience (Azure + AWS).
Knowledge of enterprise security & compliance frameworks.
Reporting Structure:
Reports directly to the Practice/Portfolio Head.
What is in it for you:
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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